WO2023011655A1 - Procédé et appareil de communication - Google Patents

Procédé et appareil de communication Download PDF

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Publication number
WO2023011655A1
WO2023011655A1 PCT/CN2022/110695 CN2022110695W WO2023011655A1 WO 2023011655 A1 WO2023011655 A1 WO 2023011655A1 CN 2022110695 W CN2022110695 W CN 2022110695W WO 2023011655 A1 WO2023011655 A1 WO 2023011655A1
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WIPO (PCT)
Prior art keywords
cell
information
terminal device
future
target
Prior art date
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PCT/CN2022/110695
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English (en)
Chinese (zh)
Inventor
耿婷婷
曾宇
Original Assignee
华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to EP22852366.8A priority Critical patent/EP4369787A1/fr
Publication of WO2023011655A1 publication Critical patent/WO2023011655A1/fr
Priority to US18/432,420 priority patent/US20240179603A1/en

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/32—Reselection being triggered by specific parameters by location or mobility data, e.g. speed data
    • H04W36/324—Reselection being triggered by specific parameters by location or mobility data, e.g. speed data by mobility data, e.g. speed data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/02—Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]; Transfer of mobility data, e.g. between HLR, VLR or external networks
    • H04W8/08—Mobility data transfer
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0061—Transmission or use of information for re-establishing the radio link of neighbour cell information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0055—Transmission or use of information for re-establishing the radio link
    • H04W36/0072—Transmission or use of information for re-establishing the radio link of resource information of target access point
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/18—Performing reselection for specific purposes for allowing seamless reselection, e.g. soft reselection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/20—Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/02—Arrangements for optimising operational condition
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/16—Performing reselection for specific purposes
    • H04W36/22—Performing reselection for specific purposes for handling the traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/24—Reselection being triggered by specific parameters
    • H04W36/30—Reselection being triggered by specific parameters by measured or perceived connection quality data
    • H04W36/304—Reselection being triggered by specific parameters by measured or perceived connection quality data due to measured or perceived resources with higher communication quality

Definitions

  • the embodiments of the present application relate to the field of communication technologies, and in particular, to a communication method and device.
  • the terminal can perform cell access.
  • the cell access includes the switching of the corresponding cell under the primary station, and the mobility of the secondary station.
  • the mobility of the secondary station includes adding, deleting or changing the corresponding cell of the secondary station. wait. For example, if the signal quality of the current serving cell of the terminal is poor, but the signal quality of the neighboring cell is good, the terminal can access the neighboring cell.
  • Cell access refers to the transfer of a terminal's wireless link connection from a source cell to a target cell under the control of network equipment, and is a basic technical means to maintain seamless mobile communication services. How the terminal performs cell handover is a problem worth studying.
  • Embodiments of the present application provide a communication method and device, so as to implement cell handover of terminal equipment.
  • a communication method is provided, the method is executed by the second network device, and may also be a component (processor, chip, circuit or others) configured in the second network device, or may be a software module, etc. , including: sending a first message to a first network device corresponding to a first target cell, where the first target cell is a predicted serving cell that the terminal device can access, and the first message is used to indicate a first reasoning result
  • the first reasoning result includes at least one of the following predicted items: future movement information of the terminal device, future business information of the terminal device, or future movement track information of the terminal device.
  • the second network device sends the AI reasoning result for determining the first target cell, that is, the first reasoning result, to the first network device.
  • the first network device may reuse the AI reasoning result or perform other operations to improve the utilization rate of the AI reasoning result.
  • the first target cell is determined according to the first reasoning result.
  • the future movement information of the terminal device includes predicted at least one of the following: information about the future cell of the terminal device, information about the residence time of the terminal device in the future cell, the The manner in which the terminal device accesses the future cell, whether the terminal device leaves the connected state in the future cell, or the prediction accuracy of the future movement information of the terminal device.
  • the future service information of the terminal device includes predicted at least one of the following: the future service type of the terminal device, the service quality QoS requirement of the future service, and the traffic volume of the future service , or the time information of the future business.
  • the method further includes: receiving feedback information from the first network device, where the feedback information includes indication information of at least one of the following: the actual Residence time information, whether the terminal device actually leaves the connected state in the first target cell, a second reasoning result, or a second target cell.
  • the feedback information is used to optimize or update parameters of a model for determining the first reasoning result.
  • the first network device can send feedback information to the network device based on the actual operating parameters of the terminal device. Based on the feedback information, the first network device may optimize or update parameters related to the AI model, for example, the AI model itself or input parameters of the AI model, so as to improve the reasoning accuracy of the AI model.
  • the first reasoning result includes a reasoning result related to the mobility of the primary cell of the terminal device, and/or a reasoning result related to the mobility of the secondary station of the terminal device.
  • the first message when the first inference result includes an inference result related to the mobility of the terminal device's primary cell, the first message includes the terminal device's source secondary station, source secondary cell Indication information whether at least one of the group, the source primary secondary cell, or the source secondary cell needs to be changed.
  • a communication method is provided.
  • the execution body of the method is the first network device, and may also be a component (processor, chip, circuit or others) configured in the first network device, or may be a software module, etc. , including: receiving a first message from a second network device, where the first message is used to indicate a first inference result, and the first inference result includes at least one of the following predicted items: future movement information of the terminal device , future service information of the terminal device, or future movement track information of the terminal device.
  • the first network device can use the first reasoning result to perform corresponding operations, thereby improving the utilization rate of the first reasoning result.
  • the first network device can directly perform AI reasoning on the basis of the first reasoning result without having to start reasoning from scratch, saving the second Computing resources and storage resources of a network device.
  • the first message is used to request the first network device to allocate resources corresponding to a first target cell for the terminal device, and the first target cell is a predicted cell that the terminal device can access. Serve the community.
  • the method further includes: allocating resources of the first target cell to the terminal equipment in response to the first message; sending the second network equipment allocated for the terminal equipment to the second network equipment. Resource indication information of a target cell.
  • the future movement information of the terminal device includes predicted at least one of the following:
  • Information about the future cell of the terminal device residence time information of the terminal device in the future cell, the way the terminal device accesses the future cell, whether the terminal device leaves the connection in the future cell state, or the prediction accuracy of the future mobile information of the terminal device.
  • the future service information of the terminal device includes predicted at least one of the following:
  • the future service type of the terminal device the service quality QoS requirement of the future service, the service volume of the future service, or the time information of the future service.
  • the method further includes: sending feedback information to the second network device, where the feedback information includes indication information of at least one of the following: the actual camping position of the terminal device in the first target cell time information, whether the terminal device actually leaves the connected state in the first target cell, the second reasoning result, or the second target cell.
  • the feedback information is used to optimize or update parameters of a model for determining the first reasoning result.
  • the first reasoning result includes a reasoning result related to the mobility of the primary cell of the terminal device, and/or a reasoning result related to the mobility of the secondary station of the terminal device.
  • the first message when the first inference result includes an inference result related to the mobility of the terminal device's primary cell, the first message includes the terminal device's source secondary station, source secondary cell Indication information whether at least one of the group, the source primary secondary cell, or the source secondary cell needs to be changed.
  • the device may be a network device, or a device in a configured network device, or a device that can be matched with the network device.
  • the device includes a one-to-one unit for performing the method/operation/step/action described in the first aspect, and the unit may be a hardware circuit, or software, or a combination of hardware circuit and software.
  • the device may include a processing unit and a communication unit, and the processing unit and the communication unit may perform corresponding functions in any design example of the first aspect above, specifically: the processing unit is configured to generate the first message; the communication A unit, configured to send a first message to a first network device corresponding to a first target cell, where the first target cell is a predicted serving cell that the terminal device can access, and the first message is used to indicate the first reasoning
  • the first reasoning result includes at least one of the following predicted items: future movement information of the terminal device, future service information of the terminal device, or future movement track information of the terminal device.
  • the device includes a memory for implementing the method described in the first aspect above.
  • the apparatus may also include memory for storing instructions and/or data.
  • the memory is coupled to the processor, and when the processor executes the program instructions stored in the memory, the method described in the first aspect above can be implemented.
  • the device may also include a communication interface for the device to communicate with other devices.
  • the communication interface may be a transceiver, circuit, bus, module, pin or other types of communication interface.
  • the device includes:
  • a processor configured to generate a first message
  • a communication interface sending a first message to a first network device corresponding to a first target cell, where the first target cell is a predicted serving cell that the terminal device can access, and the first message is used to indicate a first reasoning result
  • the first reasoning result includes at least one of the following predicted items: future movement information of the terminal device, future business information of the terminal device, or future movement track information of the terminal device.
  • the device may be a network device, or a device configured in the network device, or a device that can be used in conjunction with the network device.
  • the device includes a one-to-one unit for performing the methods/operations/steps/actions described in the second aspect.
  • the unit may be a hardware circuit, or software, or a combination of hardware circuit and software.
  • the apparatus may include a processing unit and a communication unit, and the processing unit and the communication unit may perform the corresponding functions in any design example of the second aspect above, specifically: the communication unit is configured to receive information from the second network device A first message, where the first message is used to indicate a first reasoning result, where the first reasoning result includes at least one of the following predicted items: future movement information of the terminal device, future business information of the terminal device, Or the future movement track information of the terminal device.
  • a processing unit configured to process the first message.
  • the device includes a memory for implementing the method described in the second aspect above.
  • the apparatus may also include memory for storing instructions and/or data.
  • the memory is coupled to the processor, and when the processor executes the program instructions stored in the memory, the method described in the second aspect above can be implemented.
  • the device may also include a communication interface for the device to communicate with other devices.
  • the communication interface may be a transceiver, circuit, bus, module, pin or other types of communication interface.
  • the device includes:
  • a communication interface receiving a first message from a second network device, where the first message is used to indicate a first reasoning result, and the first reasoning result includes at least one of the following predicted items: future movement information of the terminal device , future service information of the terminal device, or future movement track information of the terminal device.
  • the processor is configured to process the first message.
  • the embodiment of the present application further provides a computer-readable storage medium, including instructions, which, when run on a computer, cause the computer to execute the method of any one of the first aspect or the second aspect.
  • the embodiment of the present application further provides a system-on-a-chip, where the system-on-a-chip includes a processor and may further include a memory, configured to implement the method in any one of the first aspect or the second aspect.
  • the system-on-a-chip may consist of chips, or may include chips and other discrete devices.
  • the embodiments of the present application further provide a computer program product, including instructions, which, when run on a computer, cause the computer to execute the method of any one of the first aspect or the second aspect.
  • the embodiment of the present application further provides a system, the system includes the device of the third aspect or the fourth aspect, and the device of the fifth aspect or the sixth aspect.
  • FIG. 1 is a schematic diagram of a communication architecture provided by an embodiment of the present application.
  • FIG. 1a to Figure 2d are schematic diagrams of the AI model provided by the embodiment of the present application.
  • FIG. 7 and Figure 8 are schematic diagrams of the device provided by the embodiment of the present application.
  • Figure 9a is a schematic diagram of the structure of a neuron
  • Fig. 9b is a schematic diagram of the layer relationship of the neural network.
  • FIG. 1 is a schematic structural diagram of a communication system 1000 applied in an embodiment of the present application.
  • the communication system includes a radio access network 100 and a core network 200 , and optionally, the communication system 1000 may also include the Internet 300 .
  • the radio access network 100 may include at least one radio access network device (such as 110a and 110b in FIG. 1 ), and may also include at least one terminal (such as 120a-120j in FIG. 1 ).
  • the terminal is connected to the wireless access network device in a wireless manner, and the wireless access network device is connected to the core network in a wireless or wired manner.
  • the core network equipment and the wireless access network equipment can be independent and different physical equipment, or the functions of the core network equipment and the logical functions of the wireless access network equipment can be integrated on the same physical equipment, or it can be a physical equipment It integrates some functions of core network equipment and some functions of radio access network equipment. Terminals and wireless access network devices may be connected to each other in a wired or wireless manner.
  • FIG. 1 is only a schematic diagram.
  • the communication system may also include other network devices, such as wireless relay devices and wireless backhaul devices, which are not shown in FIG. 1 .
  • the radio access network equipment can be a base station (base station), an evolved base station (evolved NodeB, eNodeB), a transmission reception point (transmission reception point, TRP), and the next generation in the fifth generation (5th generation, 5G) mobile communication system
  • Base station (next generation NodeB, gNB), the next generation base station in the sixth generation (6th generation, 6G) mobile communication system, the base station in the future mobile communication system or the access node in the wireless fidelity (wireless fidelity, WiFi) system etc.; it can also be a module or unit that completes some functions of the base station, for example, it can be a centralized unit (central unit, CU) or a distributed unit (distributed unit, DU).
  • the CU here completes the functions of the base station's radio resource control (radio resource control, RRC) protocol and packet data convergence protocol (PDCP), and can also complete the service data adaptation protocol (service data adaptation protocol, SDAP)
  • RRC radio resource control
  • PDCP packet data convergence protocol
  • SDAP service data adaptation protocol
  • the function; the DU completes the functions of the radio link control (radio link control, RLC) layer and medium access control (medium access control, MAC) layer of the base station, and can also complete part of the physical (PHY) layer or all physical layers.
  • RLC radio link control
  • MAC medium access control
  • PHY physical
  • the radio access network device may be a macro base station (such as 110a in Figure 1), a micro base station or an indoor station (such as 110b in Figure 1), or a relay node or a donor node.
  • the embodiment of the present application does not limit the specific technology and specific equipment form adopted by the radio access network equipment.
  • a base station is used as an example of a radio access network device for description below.
  • a terminal may also be called terminal equipment, user equipment (user equipment, UE), mobile station, mobile terminal, and so on.
  • Terminals can be widely used in various scenarios, such as device-to-device (D2D), vehicle-to-everything (V2X) communication, machine-type communication (MTC), Internet of Things ( internet of things, IOT), virtual reality, augmented reality, industrial control, autonomous driving, telemedicine, smart grid, smart furniture, smart office, smart wearables, smart transportation, smart city, etc.
  • Terminals can be mobile phones, tablet computers, computers with wireless transceiver functions, wearable devices, vehicles, drones, helicopters, airplanes, ships, robots, robotic arms, smart home devices, etc.
  • the embodiment of the present application does not limit the specific technology and specific device form adopted by the terminal.
  • UE is used as an example of a terminal for description below.
  • Base stations and terminals can be fixed or mobile. Base stations and terminals can be deployed on land, including indoors or outdoors, handheld or vehicle-mounted; they can also be deployed on water; they can also be deployed on aircraft, balloons and artificial satellites in the air. The embodiments of the present application do not limit the application scenarios of the base station and the terminal.
  • the helicopter or UAV 120i in FIG. base station for base station 110a, 120i is a terminal, that is, communication between 110a and 120i is performed through a wireless air interface protocol.
  • communication between 110a and 120i may also be performed through an interface protocol between base stations.
  • 120i compared to 110a, 120i is also a base station. Therefore, both the base station and the terminal can be collectively referred to as a communication device, 110a and 110b in FIG. 1 can be referred to as a communication device with a base station function, and 120a-120j in FIG. 1 can be referred to as a communication device with a terminal function.
  • the communication between the base station and the terminal, between the base station and the base station, and between the terminal and the terminal can be carried out through the licensed spectrum, the communication can also be carried out through the unlicensed spectrum, and the communication can also be carried out through the licensed spectrum and the unlicensed spectrum at the same time; Communications may be performed on frequency spectrums below megahertz (gigahertz, GHz), or communications may be performed on frequency spectrums above 6 GHz, or communications may be performed using both frequency spectrums below 6 GHz and frequency spectrums above 6 GHz.
  • the embodiments of the present application do not limit the frequency spectrum resources used for wireless communication.
  • the functions of the base station may also be performed by modules (such as chips) in the base station, or may be performed by a control subsystem including base station functions.
  • the control subsystem including base station functions here may be the control center in the above application scenarios such as smart grid, industrial control, intelligent transportation, and smart city.
  • the functions of the terminal may also be performed by a module (such as a chip or a modem) in the terminal, or may be performed by a device including the terminal function.
  • the base station sends a downlink signal or downlink information to the terminal, and the downlink information is carried on the downlink channel;
  • the terminal sends an uplink signal or uplink information to the base station, and the uplink information is carried on the uplink channel.
  • the terminal needs to establish a wireless connection with the cell controlled by the base station.
  • a cell with which a terminal has established a wireless connection is called a serving cell of the terminal.
  • the terminal communicates with the serving cell, it will also be interfered by signals from neighboring cells.
  • a UE may switch serving cells.
  • the base station to which the UE's current serving cell belongs may be referred to as a source base station
  • the base station to which the UE's serving cell to be switched belongs to may be referred to as a target base station.
  • the source base station or the AI device can perform artificial intelligence (AI) reasoning to determine the AI target cell, and send a handover request to the base station corresponding to the AI target cell, called the target base station. Afterwards, if the target base station agrees to the handover request of the source base station, the UE can be handed over to the AI target cell.
  • AI artificial intelligence
  • the above AI reasoning results can be sent to the target base station corresponding to the AI target cell in the handover request. Subsequently, the base station corresponding to the AI target cell can use the AI reasoning result to perform a series of operations, thereby improving the utilization rate of the AI reasoning result.
  • the embodiment of the present application involves the process of predicting the serving cell to which the UE can handover by using the AI technology
  • the AI technology is firstly introduced for ease of understanding. It should be understood that this introduction is not intended to limit the embodiments of the present application.
  • AI is a technology that performs complex calculations by simulating the human brain. With the improvement of data storage and capabilities, AI has been applied more and more.
  • the 3rd generation partnership project ( 3rd generation partnership project, 3GPP) version 17 (release17, R17) has passed the research project (study item, SI), and proposes to apply AI to new radio (new radio, NR).
  • Figure 2a is an example diagram of the first application framework of AI in NR:
  • Data source is used to store training data and inference data.
  • the model training host (model training host) obtains the AI model by analyzing or training the training data provided by the data source, and deploys the AI model in the model inference host (model inference host).
  • the model inference node uses the AI model to perform inference based on the inference data provided by the data source, and obtains the inference result.
  • the reasoning results are used to give reasonable predictions based on AI for network operation, or guide the network to make policy configurations or policy adjustments. Relevant policy configuration or policy adjustment is uniformly planned by the execution (actor) entity, and sent to multiple execution objects (for example, network entities) for execution. At the same time, after the relevant strategies are applied, the specific performance of the network can be input to the data source again for storage.
  • Figure 2b, Figure 2c or Figure 2d is an example diagram of the second application framework of AI in NR:
  • a first AI module independent of the base station receives training data.
  • the first AI module obtains an AI model by analyzing or training the training data.
  • the first AI module may use the corresponding AI model and reasoning data to perform inference to obtain the parameter, as shown in Figure 2b; or the first AI module may send the information of the AI model to the base station
  • the second AI module (or described as located in the RAN) uses the corresponding AI model and inference data to perform inference to obtain the parameter, as shown in FIG. 2c.
  • the AI model used by the second AI module for reasoning may also be obtained by the second AI module receiving training data and performing training on the training data, as shown in FIG. 2d.
  • the AI model can be simply referred to as a model, which can be regarded as a mapping from input measurement quantities (measurement information) to output parameters.
  • the input measurement can be one or more measurements
  • the output parameter can be one or more parameters.
  • the training data may include known input measurements, or known input measurements and corresponding output parameters, for training the AI model.
  • the training data may be data from the base station, CU, CU-CP, CU-UP, DU, radio frequency module, UE and/or other entities, and/or data inferred by AI technology, without limitation.
  • Inference data includes input measurements that are used to infer parameters using the model.
  • Inference data may be data from a base station, CU, CU-CP, CU-UP, DU, radio module, UE and/or other entities.
  • the inferred parameters can be regarded as policy information and sent to the execution object.
  • the inferred parameters can be sent to the base station, CU, CU-CP, CU-UP, DU, radio frequency module, or UE, etc. for policy configuration or policy adjustment.
  • the AI models used for inferring different parameters can be the same or different without limitation.
  • the UE and/or the base station may perform some or all of the steps in the embodiment of the present application, these steps or operations are only examples, and the embodiment of the present application may also perform other operations or various operations deformation.
  • each step may be performed in a different order presented in the embodiment of the present application, and it may not be necessary to perform all operations in the embodiment of the present application.
  • this embodiment of the present application provides a flow of a communication method, which at least includes:
  • Step 300 the source base station determines a first inference result, and the first inference is also called an AI inference result, a first AI inference result or other names, etc., which are not limited.
  • an AI model is deployed in the source base station, and the AI model can refer to the introduction in FIG. 2a, FIG. 2c or FIG. 2d.
  • the source base station may perform AI reasoning based on the AI model to obtain a first reasoning result.
  • the source base station may use at least one of the following information as the input of the AI model, for example, historical trajectory information of the UE, historical residence information of the UE, current moving direction of the UE, speed of the UE, network information subscribed by the UE (for example, telecommunications, China Unicom or China Mobile, etc.), or the service requirements of the UE, etc., are input into the AI model, and the output of the AI module is the first reasoning result.
  • the AI device is deployed separately, and the AI device may be called a remote intelligent communication, a wireless intelligent controller, an AI node, or others, without limitation.
  • An AI model is deployed in the AI device, and the AI model may refer to the introduction in FIG. 2a or FIG. 2b.
  • the AI device may perform AI reasoning based on the AI model, determine a first reasoning result, and send indication information of the first reasoning result to the source base station.
  • the AI model in this application can be composed of various deep neural networks.
  • a neural network is a specific implementation of machine learning. Neural networks can be used to perform classification tasks, prediction tasks, and can also be used to establish conditional probability distributions among variables.
  • DNN deep neural network
  • GNN generative neural network
  • FNN feedforward neural network
  • CNN convolutional neural network
  • RNN recurrent neural network
  • GNN includes Generative Adversarial Network (GAN) and Variational Autoencoder (VAE).
  • GAN Generative Adversarial Network
  • VAE Variational Autoencoder
  • each neuron performs a weighted summation operation on its input values, and the weighted summation result is passed through an activation function to generate an output.
  • Fig. 9a is a schematic diagram of neuron structure.
  • the bias of the weighted sum Set to b the form of the activation function can be diversified.
  • DNN generally has a multi-layer structure. Each layer of DNN can contain multiple neurons. The input layer passes the received value to the middle hidden layer after being processed by neurons. Similarly, the hidden layer then passes the calculation result to the final output layer to generate the final output of the DNN. As shown in Fig. 9b, Fig. 9b is a schematic diagram of the layer relationship of the neural network. DNN generally has one or more hidden layers, and hidden layers often directly affect the ability to extract information and fit functions.
  • the parameters of each neuron include weights, biases and activation functions, and the set of parameters of all neurons in DNN is called DNN parameters (or called neural network parameters).
  • DNN parameters or called neural network parameters.
  • the weights and biases of neurons can be optimized through the training process, so that DNN has the ability to extract data features and express mapping relationships.
  • the parameters of the neural network include information related to the neural network, for example, may include one or more of the following:
  • the type of neural network such as a deep neural network, or a generative neural network
  • Information related to the neural network structure such as the type of the neural network, the number of layers of the neural network, the number of neurons, etc.;
  • the parameters of each neuron in the neural network such as weights, biases, and activation functions.
  • the first reasoning result includes at least one of the following: future mobility information of the UE, future service information of the UE, or prediction information of a moving trajectory of the UE.
  • the UE's movement track prediction information may refer to predicted geographic location information of the UE in the future.
  • the UE's movement track prediction information may be predicted location information A of the UE at a first time in the future, location information B of the UE at a second time in the future, and so on.
  • the predicted future mobility information and/or future business service information of the UE is obtained.
  • the UE's future mobility information may include predicted at least one of the following information:
  • the information of the future cell of the UE may be the information of the cell that the UE may access in the future time.
  • the UE's future cell information may include cell 1 to cell 10 and so on.
  • Information about each cell may include cell global identifier (CGI), physical cell identifier (PCI) and frequency point, cell identifier (cell ID), non-public network identifier ( At least one of non-public network identifier, NPN ID), non-terrestrial network identifier (non-terrestrial network identifier, NTN ID) or other cell identifiers.
  • the CGI may include a public land mobile network (public land mobile network, PLMN ID) and a cell ID.
  • the information of the cell may also include a tracking area code (tracking area code, TAC) and/or identification information of a network device to which the cell belongs, such as a global network device identification.
  • TAC tracking area code
  • the dwell time information may refer to the time when the UE receives service in a certain cell, or the time when a certain cell is used as a serving cell, etc.
  • the residence time is specifically the start time and end time of receiving services in the cell.
  • the start time may be called the start time stamp time
  • the end time may be called the end time stamp time, etc., or may be The length of time for the UE to receive services in the cell, which may be referred to as a time range or the like.
  • the information of the future cells may be sorted according to the dwell time of the UE in different future cells.
  • the manner in which the UE camps on the cell may be: the UE handovers to the cell, or the UE selects and accesses the cell, or the UE reselects to the cell, or the UE reestablishes to the cell, etc.
  • the way the UE accesses the future cell may include normal handover (legacy handover or ordinary handover), dual active protocol stack handover (dual active protocol stack handover, DAPS HO), conditional handover (conditional handover, CHO), no random Access handover (RACH-less HO) or other access methods, etc.
  • normal handover legacy handover or ordinary handover
  • dual active protocol stack handover dual active protocol stack handover
  • conditional handover conditional handover, CHO
  • RACH-less HO no random Access handover
  • the information may specifically be whether the predicted UE will leave the connected state in the future cell. For example, if it is predicted that the UE will leave the connected state in the future cell, it can be represented by a first value (such as 1); if it is predicted that the UE will not leave the connected state in the future cell, it can be represented by a second value (such as 0).
  • a first value such as 1
  • a second value such as 0
  • the first value (such as 00) can be used to identify it; if it is predicted that the UE will leave the connected state and enter the idle state in the future cell, it can be Use the second value (for example, 01) to indicate; if it is predicted that the UE will not leave the connected state in the future cell, it can be indicated by the third value (for example, 11).
  • the information about the future cell of the UE, information about the residence time of the UE in the future cell, the manner in which the UE accesses the future cell, and whether the UE leaves the connected state in the future cell can all be referred to as future mobility information of the UE.
  • future mobility information of the UE For each item of information in the above UE's future mobility information, an accuracy can be predicted.
  • an accuracy at the cell level may be comprehensively predicted.
  • all future cells include cell 1 to cell 10 .
  • the prediction accuracy of the cell can be obtained comprehensively. For example, the comprehensive prediction accuracy of cell 1 is 95%, the comprehensive prediction accuracy of cell 2 is 98%, and so on.
  • the future service information of the UE includes predicted at least one of the following: the future service type of the UE, the service quality (quality of service, QoS) requirement of the UE's future service, the service volume of the future service, or the future service time information, etc.
  • Historical input information X his (0, N)
  • trajectory information including one or more of the following: trajectory information, resident information, moving direction, speed, contracted network information (for example, China Telecom, China Unicom or China Mobile, etc.), or UE The service requirements, etc., and the actual output information Y his corresponding to the historical input of the UE, such as the information of the cell actually accessed or camped on, the way of accessing the cell, etc.
  • the historical input information X his (0,x+1) of [T 0 ,...,T x ] can be selected as the input of the DNN model, and the inference information Y inf of [T x+1 ] can be obtained (x+1).
  • the loss function L(x+1) is obtained by comparing Y inf (x+1) with Y his (x+1).
  • the calculation method of the loss function can be, for example, commonly used mean square error loss, KL divergence (Kullback–Leibler divergence) loss, etc., which is not limited in this solution.
  • p means The number of parameters in , that is, the number of items of actual output information corresponding to historical input, Indicates the value of parameter i at (x+1) time, Indicates the inferred value of parameter i at time (x+1).
  • the accuracy of the current inference can be judged, wherein the setting of the specific preset threshold can be based on system requirements. For example, when the loss function value corresponding to the inference result at a certain moment is greater than the preset threshold 5, it is considered that the parameters of the model need to be adjusted to reduce the loss function value.
  • the model is adjusted so that the loss function at all moments is lower than the target loss function value, that is, the aforementioned preset threshold, it can be considered based on [T 0 ...T x ,T x+1 ...T N ]
  • the historical input, the actual output corresponding to the historical input, and the inference results of the historical input, the model has been trained and converged, and it is a usable model, that is, it can be applied to prediction.
  • Step 301 The source base station determines a first target cell according to a first reasoning result, and the first target cell may also be called an AI target cell. Alternatively, it may be described as that the first target cell is determined according to the first reasoning result.
  • the first target cell is a predicted serving cell that the UE can access.
  • the source base station may select a cell from the future cell information in the first reasoning result as the first target cell.
  • the future cell information in the first reasoning result includes cell 1 to cell 10 .
  • the source base station may select cell 1 as the first target cell.
  • the source base station can consider the mobility trajectory information of the UE. In the future, the UE will appear in the service range of cell 1, or the source base station can determine that the UE is in cell 1 based on the information about the residence time of the UE in the future cell.
  • the residence time of the cell is the longest or relatively long, select cell 1 as the first target cell, etc.
  • Step 302 The source base station sends a first message to a target base station corresponding to the first target cell, where the first message is used to indicate a first inference result.
  • the first message may be a handover request message or other messages, which is not limited.
  • the source base station may indicate all or part of the information of the first reasoning result in the foregoing first message. That is, the source base station may notify the target base station of all or part of the information of the first inference result.
  • the future cell information in the first reasoning result includes cell 1 to cell 10, and the source base station selects cell 1 as the first target cell.
  • the source base station may notify the target base station of the information about cells 2 to 10 in the first reasoning result.
  • Step 303 The source base station receives a second message from the target base station.
  • the second message is used to indicate whether the target base station agrees to the handover request of the source base station.
  • the second message may be called a handover response message or other messages.
  • the above second message may be an affirmative response message, for example, a handover request acknowledge (handover request acknowledge) message.
  • the first target cell does not agree to the handover request of the source base station, that is, does not agree to the handover of the UE to the first target cell
  • the above-mentioned second message may be a negative response message, such as a handover preparation failure (handover preparation failure) message, or Handover failure (handover failure) message, etc.
  • the target base station may allocate resources of the first target cell for the UE in response to the first message, and send information about resources of the first target cell allocated to the UE to the source base station Instructions.
  • the resource indication information of the first target cell may be carried in the second message.
  • the source base station may indicate to the UE the resource of the first target cell allocated to the UE.
  • the UE can access the first target cell. For example, after the UE accesses the first target cell, the target base station corresponding to the first target cell may use actual information after the UE accesses the target base station.
  • feedback information may be sent to the source base station, or feedback information may be sent to the source base station based on other conditions, without limitation.
  • specific trigger conditions for sending feedback information please refer to the description in step 304, so that the AI model determined by the source base station or the AI device for the first inference result is optimized or updated to make the inference of the AI model more accurate.
  • Step 304 The target base station sends indication information of the feedback information to the source base station or the AI device.
  • the target base station sends feedback information indication information to the source base station, and the source base station updates the parameters of the AI model based on the feedback information.
  • the target base station may send indication information of the feedback information to the source base station, and the source base station sends all or part of the feedback information to the AI device.
  • the target base station may directly send the feedback information to the AI device through an interface between the target base station and the AI device.
  • the first message in step 302 above may carry information about the AI device, for example, the address information of the AI device, or the address information of the AI device.
  • the AI device Based on the feedback information, the AI device optimizes or adjusts the parameters of the AI model.
  • the feedback information is used to optimize or update the parameters of the model for determining the first reasoning result.
  • the input parameters of the AI model may be updated or prioritized according to the above feedback information, and/or the AI model itself may be optimized or updated, etc., without limitation.
  • the target base station can send feedback information to the source base station or the AI device when at least one of the following trigger conditions is met:
  • the target base station determines to handover the UE to the second target cell. For example, due to factors such as UE movement, the first target base station considers that the UE needs to be handed over from the first target cell to the second target cell. Regarding the manner in which the target base station determines the second target cell, it may be: the first target cell performs AI inference based on the AI model, and determines the second inference result. Alternatively, the AI device performs AI reasoning based on the AI model, determines a second reasoning result, and sends indication information of the second reasoning result to the first target cell. The first target cell determines the second target cell, etc. based on the second reasoning result. For example, the first target cell is cell 1, and the second target cell is cell 2. When the base station corresponding to cell 1 determines that the UE needs to be handed over to cell 2, the base station corresponding to cell 1 considers that the trigger condition is satisfied, and the base station corresponding to cell 1 can send feedback information to the source base station.
  • the service information of the UE in the first target cell changes.
  • the target base station may compare the service information of the UE in the first target cell with the service information predicted in the first reasoning result. When the difference between the two exceeds a certain range, it can be considered that the trigger condition is met, and feedback information can be sent to the source base station.
  • the second target cell determined by the target base station is different from the predicted cell in the received first reasoning result.
  • the second target upper area does not belong to the cell in the future cell information of the first inference result.
  • the future cell information in the first pushing result includes cell 1 to cell 10
  • the target base station determines that the cell to be handed over to by the UE next time is cell 20, it can be considered that the trigger condition is met, and feedback information can be sent to the source base station.
  • the access mode of the UE predicted by the target base station in the second target cell is different from the access mode predicted in the first reasoning result.
  • the target base station may determine the second reasoning result.
  • the second target cell and the access manner in the second target cell may be determined according to the second reasoning result.
  • the predicted access modes in the first reasoning result may include A, B, and C, and so on.
  • the UE access mode predicted by the target base station is F, it can be considered that the trigger condition is met, and feedback information can be sent to the source base station.
  • the UE's actual trajectory deviates from the UE's movement trajectory predicted in the first inference result.
  • the UE movement track predicted in the first reasoning result is that at the first time, the UE is predicted to be at position A; at the second time, the UE is predicted to be at position B; but at the first time, the UE is actually at position C; when the position When the distance between A and position C is greater than the preset condition, it can be considered that the trigger condition is met, and feedback information can be sent.
  • the feedback information sent by the target base station to the source base station or the AI device may include at least one of the following:
  • the information may be information about the actual residence time of the UE in cell 1.
  • the actual dwell time information may be the actual start time and the actual end time of the UE's stay in the cell 1 .
  • the actual resident time information may be the actual resident duration information of the UE in the cell 1 and the like.
  • the target base station may determine the second reasoning result according to the first reasoning result sent by the source base station.
  • the target base station may input the first inference result into the AI model as an input of the AI model, and the output of the AI model is the second inference result.
  • the target base station may send the first inference result to the AI device, and the AI device performs AI inference based on the first inference result, determines the second inference result, and sends the second inference result to the target base station and so on.
  • the type of information included in the second reasoning result refer to the description of the first reasoning result above.
  • the target base station determines the second target cell according to the second reasoning result.
  • the future cell information included in the second reasoning result is cell 2 to cell 10
  • the second target cell determined by the target base station may be cell 2 and so on.
  • the service type of the UE in the second target cell or the manner of accessing the second cell may be predicted by the target base station. For example, it may be predicted or inferred by the target base station based on the first inference result.
  • step 300, step 301, step 303 or step 304 in the process shown in FIG. 3 are all optional.
  • the source base station indicates the first reasoning result to the target base station.
  • the first target device can directly use the first reasoning result to perform AI reasoning to determine the second reasoning result; and determine the second target cell based on the second reasoning result. Since the source base station or the AI device consumes a lot of computing resources or storage resources when inferring the first inference result, doing so can improve the utilization rate of the first inference result. Furthermore, the first target device directly uses the first inference result to perform AI inference without inferring from scratch, which can also reduce the consumption of computing resources or storage resources of the first target device.
  • the first target cell may determine a trigger condition for feedback information according to the first reasoning result.
  • feedback information may be sent to the source base station or the AI device. Based on the feedback information, the parameters of the AI model are optimized or updated to improve the accuracy of subsequent AI reasoning and improve system efficiency.
  • the source base station sends the first reasoning result to the target base station in step 302 above.
  • How the target base station or other devices use the first reasoning result is not limited in this embodiment of the present application.
  • the above process of using the first reasoning result is only a schematic illustration.
  • the dual connectivity technology of the UE is firstly introduced.
  • the UE maintains connections with two base stations at the same time and receives services, which is called a dual connectivity architecture.
  • the dual connection architecture supported in the NR system also known as multi-radio dual connectivity (MR-DC) includes: dual connections composed of LTE base stations and NR base stations, or composed of NR base stations and NR base stations dual connectivity, or dual connectivity composed of an LTE base station and an LTE base station, etc.
  • the LTE base station includes an LTE base station connected to 4G core network equipment, or an LTE base station connected to 5G core network equipment.
  • NR base stations include NR base stations connected to 4G core network equipment, or NR base stations connected to 5G core network equipment.
  • the UE can maintain connections with two base stations, which are called a master node (MN) and a secondary node (SN) respectively.
  • MN master node
  • SN secondary node
  • the primary cell group includes at least one cell.
  • the primary cell group may include a primary cell (primary cell, PCell), and may also include at least one secondary cell (secondary cell, SCell) when carrier aggregation (carrier aggregation, CA) is configured.
  • the cell group in which the secondary station provides air interface resources for the UE is called a secondary cell group (SCG).
  • the secondary cell group includes at least one cell.
  • the secondary cell group may include a primary secondary cell (PSCell), and may also include at least one secondary cell when CA is configured.
  • a flow of a communication method is provided.
  • the flow may be a specific application of the flow shown in FIG. 3 in a dual connection architecture, and at least includes the following steps:
  • Step 400 The source master station determines the first reasoning result.
  • the first reasoning result may include a reasoning result related to primary cell mobility and/or a reasoning result related to SN mobility.
  • the inference result related to the mobility of the primary cell and the inference result related to the SN mobility may be inferred by using the same AI model, or may be inferred by using different AI models, etc., without limitation.
  • the reasoning results related to the mobility of the primary cell and the reasoning results related to the SN mobility may be derived by the source master station based on the AI model, or by the AI device based on the AI model. Or, any one of the above two inference results is inferred by the source master station, and the other one is inferred by the AI device, etc., without limitation.
  • the inference result related to the mobility of the primary cell may include at least one of the following: mobility information of the UE's future primary cell/primary station/primary cell group, future service information of the UE in the future primary cell/primary station/primary cell group, Or UE's movement trajectory prediction information, etc.
  • the reasoning results related to SN mobility may include at least one of the following: mobility information of the UE's future primary secondary cell/secondary station/secondary cell group, future service information of the UE in the future primary secondary cell/secondary station/secondary cell group, or Mobile trajectory prediction information of the UE, etc.
  • Step 401 The source primary station determines a first target primary cell based on a first reasoning result, and the first target primary cell is a predicted primary cell that the UE can access.
  • the source primary station may determine the first target primary cell according to the inference result related to the mobility of the primary cell in the first inference result.
  • the future primary cells in the inference result related to the mobility of the primary cell include primary cell 1 to primary cell 10 .
  • the source master station finds through judgment that the primary cell 1 can be used as the primary cell of the UE, and then the primary cell 1 can be regarded as the above-mentioned first target primary cell.
  • Step 402 The source primary station sends a first message to the base station corresponding to the first target primary cell, and the base station corresponding to the first target primary cell may be called a target primary station.
  • the first message is used to request handover of the primary cell of the UE to the first target primary cell, and the first message may include indication information of the above-mentioned first reasoning result.
  • the first message may include at least one of the mobility inference result of the primary cell and the mobility inference result of the SN. If the target base station agrees to the request of the first message, the target base station may configure information related to the primary cell for the UE when receiving the mobility inference result of the primary cell, for example, configure a primary cell group for the UE. After the UE accesses the first target primary cell, the first target primary cell can add, change or delete secondary stations for the UE according to the mobility reasoning result of the SN.
  • the target master station after the target master station changes or adds a secondary station for the UE, it can also add or update the relevant information of the secondary station for the UE configuration according to the reasoning results related to the SN mobility, for example, for the added or updated secondary station configuration Relevant information of the secondary cell group, etc. or,
  • the target master station can determine the triggering condition of the feedback information of the reasoning result related to the mobility of the primary cell according to the reasoning result related to the mobility of the primary cell. For example, when the difference between the predicted information in the reasoning results related to the main cell and the actual information after the UE accesses the first main station exceeds the preset value, the target main station can send feedback information to the source base station or AI equipment, etc., To optimize or update the parameters related to the AI model. Similarly, the target master station may also determine the triggering conditions of the feedback information of the SN mobility-related reasoning results according to the SN mobility-related reasoning results.
  • the first message may include the source secondary station, source secondary cell group, and source primary secondary cell of the terminal device. Or indication information indicating whether at least one item in the source secondary cell needs to be changed.
  • Step 403 The source master station receives a second message from the target master station, and the second message may be a response message to the above-mentioned first message.
  • the second message may be an acknowledgment message, indicating that the target primary station agrees to the request of the source primary station, and the primary cell of the UE may be handed over to the first target primary cell.
  • the primary cell of the UE is handed over to the first target primary cell, and it can be considered that the primary station of the UE is handed over from the source primary station to the target primary station.
  • the target primary station agrees to the UE's request, it can determine the relevant configuration of the primary station according to the reasoning result of the mobility of the primary cell. For example, after switching the target master station to the master station, the configuration of the master cell group, etc.
  • the relevant configuration of the master station may be carried in the second message in step 403 above.
  • the target primary station can configure the relevant information of the secondary station for the UE according to the reasoning result related to the mobility of the SN.
  • the second message may be a negative response message, indicating that the target primary station does not agree to the request of the source primary station, and the primary cell of the UE cannot be handed over to the first target primary cell.
  • Step 404 The target master station sends feedback information to the source master station or the AI device, where the feedback information is used to update or optimize the parameters of the AI model used to determine the first inference result.
  • the feedback information may include feedback information on inference results related to the mobility of the primary cell, and/or feedback information on inference results related to SN mobility.
  • the related description in step 304 which will not be repeated here.
  • the difference from the above is that if the reasoning results related to the mobility of the main cell and the reasoning results related to the SN mobility are inferred from different AI models, the above reasoning results related to the mobility of the main cell are used for the corresponding AI model
  • the parameters are optimized or updated.
  • the inference results related to SN mobility are used to optimize or update the parameters of the corresponding AI model.
  • the relevant description in step 304 which will not be repeated here.
  • the target master station sends the feedback information of the above-mentioned first reasoning result to the source master station or AI device, and the source master station or AI device can optimize or update the relevant parameters of the AI model of the first reasoning result based on the above-mentioned feedback information , so that the deduced configuration of the primary cell to be handed over by the UE or the mobility of the SN is more accurate. Further, the target master station or the source master station can configure more reasonable multi-connection configuration for the UE according to whether SN mobility is configured for the UE according to the first reasoning result, and upgrade system information.
  • a flow of a communication method is provided, which is mainly used for adding or changing UE secondary stations triggered by the primary station, and at least includes the following steps:
  • Step 500 the master station determines a first reasoning result.
  • the first reasoning result may include a reasoning result related to SN mobility.
  • the reasoning results related to SN mobility reference may be made to step 400, which will not be repeated here.
  • Step 501 the primary station determines the first target secondary station according to the first reasoning result.
  • the primary station may determine whether to add or change the secondary station of the UE according to the first reasoning result. For example, based on the future trajectory information of the UE in the inference results related to SN mobility, the primary station determines that the current secondary station cannot provide services for the UE in the future, or the service quality of the current secondary station cannot meet the requirements in the future, etc.
  • the primary station can determine the first target secondary station according to the method. For example, the primary station may determine the first target secondary station according to information such as the future primary-secondary cell/secondary station/primary-secondary cell group in the inference results related to SN mobility.
  • the master station discovers that the future cells 1 to 3 in the reasoning results related to SN mobility can be used as the secondary cell group of the UE in the future, and the base stations corresponding to the above cells 1 to 3 can be called the first target secondary cells. stand.
  • Step 502 the primary station sends a first message to the first target secondary station, the first message may be a request message requesting to add or change the first target secondary station to a secondary station of the UE, and the first message may include the first reasoning An indication of the result.
  • the first target secondary station when the first target secondary station agrees to be changed or added as a UE secondary station, the first target secondary station can determine the information related to the secondary station configured for the SN according to the first reasoning result, for example, the secondary station Cell group information, primary and secondary cell information, or secondary cell information, etc. Or, after the UE accesses the first target secondary station, the first target secondary station may perform AI reasoning according to the first reasoning result to determine future target secondary stations that the UE may add or change.
  • Step 503 the primary station receives the second message from the first target secondary station.
  • the second message may be an acknowledgment message, indicating that the first target secondary station agrees to be added or changed as a secondary station of the UE.
  • the second message may be a negative response message, indicating that the first target secondary station does not agree to be added or changed as a secondary station of the UE.
  • the second message may include secondary station related information configured by the first target secondary station for the UE, for example, secondary cell group information, primary and secondary Cell information or secondary cell information, etc.
  • the first target secondary station may notify the master station of the secondary station-related information configured for the UE through the second message, and the master station forwards it to the UE.
  • the first target secondary station may directly notify the UE of the information related to the secondary station configured above, without limitation.
  • Step 504 the first target secondary station sends feedback information to the primary station or the AI device.
  • the first target secondary station can optimize or update the parameters related to the AI model for inferring SN mobility according to the above feedback information.
  • this is based on the reasoning of the SN mobility obtained by the main station according to the AI model. under the premise of the result.
  • the first target secondary station can directly send the above feedback information to the AI device, or can send it to the master station, and the master station forwards it to the AI device wait.
  • steps 500, 501, 503 or 504 may be optional.
  • the source secondary station obtains the first target secondary station according to the first reasoning result. Afterwards, the source secondary station notifies the master station of the first reasoning result and the first target secondary station, and the master station then triggers the process of adding or changing the first target secondary station, which at least includes the following steps:
  • Step 600 the source secondary station determines the first reasoning result.
  • the first reasoning result may include a reasoning result related to SN mobility.
  • the reasoning results related to SN mobility reference may be made to step 400, which will not be repeated here.
  • the first reasoning result may be obtained by the source secondary station according to the AI model reasoning, or the AI device reasoning according to the AI model, and then notifying the source secondary station.
  • Step 601 The source secondary station determines the first target secondary station based on the first reasoning result.
  • Step 602 the source secondary station sends the first inference result and the indication information of the first target secondary station to the master station.
  • the source secondary station may only send the indication information of the first reasoning result to the primary station.
  • the primary station determines the first target secondary station according to the first reasoning result.
  • the indication information of the first target secondary station may be identification information of the first target secondary station, such as a global node identifier.
  • Step 603 the primary station sends a first message to the first target secondary station, the first message includes indication information of the first inference result, and the first message is used to request to add or change the first target secondary station as a secondary station of the UE stand.
  • Step 604 the primary station receives a second message from the first target secondary station, and the second message may be a response message to the first message.
  • Step 605 the first target secondary station sends indication information of the feedback message to the primary station.
  • Step 606 the primary station sends the indication information of the feedback message to the source secondary station.
  • the first target secondary station may send the indication information of the feedback information to the primary station, and the primary station forwards it to the source secondary station.
  • the source secondary station optimizes or updates the AI model that infers the inference result related to the mobility of the SN.
  • the first target secondary station may directly send the indication information of the feedback information to the source secondary station.
  • the first message in step 603 may need to carry address information or identification information of the source secondary station.
  • the first target secondary station can directly send the indication information of the feedback information to the AI device, or forward it to the AI device via the primary station and the source secondary station.
  • Equipment, etc. are not limited.
  • step 601 if the source base station determines to release the source base station according to the first reasoning result. Then the source secondary station may also send release instruction information to the master station, and the master station forwards the release instruction information to the UE source secondary station. Optionally, after releasing the source secondary station, the master station may send indication information of a feedback message to the source secondary station.
  • steps in the various processes described in FIG. 3 to FIG. 6 are not all the steps that need to be executed, and some steps can be added or deleted based on the actual needs of each process. For example, steps 300, 301, 303 and 304 in the above-mentioned process of FIG. 3 can be selectively executed.
  • FIG. 3 to FIG. 6 a hardware device as a whole is used as an example to describe, and actions of various modules inside the hardware device are not described.
  • the operations between internal modules of the hardware device and the operations of each module are also within the protection scope of the embodiments of the present application.
  • functions of an access network device may be implemented by multiple modules of common standards.
  • the functions of a base station may be implemented by a CU module or a DU module.
  • the actions of the source base station may be described as a whole: the source base station determines the first reasoning result, determines the first target cell according to the first reasoning result, and sends the first target cell to the target base station.
  • the entire processing process shown in Figure 3 may include: the CU determines the first inference result, determines the first target cell according to the first inference result; sends the first inference result to the DU ; The DU sends a first message to the target base station, where the first message includes indication information of the first reasoning result.
  • the description of "carrying certain indication information in a message" is adopted.
  • the indication information of the first reasoning result and the like are carried in the first message.
  • the message may directly indicate the corresponding information, for example, the information is directly carried in the message.
  • the message may indirectly indicate corresponding information.
  • the message A includes indication information of the information X
  • the data A may directly indicate the information X, for example, the data A carries the information X.
  • this data A may indicate information X indirectly.
  • the data A may carry other information of the information X and the like.
  • the apparatus 700 may include: a communication unit 701 configured to support communication between the apparatus 700 and other devices.
  • the communication unit 701 is also referred to as a transceiver unit, and may include a receiving unit and/or a sending unit, configured to perform receiving and sending operations respectively.
  • the processing unit 702 is configured to support the device to perform processing.
  • the device 700 may further include a storage unit 703 for storing program codes and/or data of the device 700 .
  • the foregoing apparatus 700 may be a network device or a module, chip or circuit in the network device.
  • the communication unit 701 is configured to execute the transceiving operation of the source base station in the flow shown in FIG. 3 above;
  • the processing unit 702 is configured to execute the processing operation of the source base station in the flow shown in FIG. 3 above.
  • the processing unit 702 is configured to generate the first message; the communication unit 701 is configured to send the first message to the first network device corresponding to the first target cell, the first target cell is predicted and the terminal device can access , the first message is used to indicate a first reasoning result, and the first reasoning result includes at least one of the following predicted items: future movement information of the terminal device, future service information of the terminal device, Or the future movement track information of the terminal device.
  • the first target cell is determined according to the first reasoning result.
  • the future movement information of the terminal device includes predicted at least one of the following: information about the future cell of the terminal device, information about the residence time of the terminal device in the future cell, the The manner in which the terminal device accesses the future cell, whether the terminal device leaves the connected state in the future cell, or the prediction accuracy of the future movement information of the terminal device.
  • the future service information of the terminal device includes predicted at least one of the following: the future service type of the terminal device, the service quality QoS requirement of the future service, and the traffic volume of the future service , or the time information of the future business.
  • the communication unit 701 is further configured to: receive feedback information from the first network device, where the feedback information includes at least one of the following indication information; Information about the actual residence time of a target cell, whether the terminal device actually leaves the connected state in the first target cell, a second reasoning result, or a second target cell.
  • the feedback information is used to optimize or update parameters of a model for determining the first reasoning result.
  • the first reasoning result includes a reasoning result related to the mobility of the primary cell of the terminal device, and/or a reasoning result related to the mobility of the secondary station of the terminal device.
  • the first message when the first inference result includes an inference result related to the mobility of the terminal device's primary cell, the first message includes the terminal device's source secondary station, source secondary cell Indication information whether at least one of the group, the source primary secondary cell, or the source secondary cell needs to be changed.
  • the foregoing apparatus 700 may be a network device or a module, chip or circuit in the network device.
  • the communication unit 701 is configured to execute the transceiving operation of the target base station in the flow shown in FIG. 3 above;
  • the processing unit 702 is configured to execute the processing operation of the target base station in the flow shown in FIG. 3 above.
  • the communication unit 701 is configured to receive a first message from a second network device, where the first message is used to indicate a first inference result, and the first inference result includes at least one of the following predictions: the terminal The future movement information of the equipment, the future service information of the terminal equipment, or the future movement track information of the terminal equipment.
  • the processing unit 702 is configured to process the first message.
  • the first message is used to request the first network device to allocate resources corresponding to a first target cell for the terminal device, and the first target cell is a predicted cell that the terminal device can access. Serve the community.
  • the processing unit 702 is further configured to allocate resources of the first target cell for the terminal device in response to the first message; the communication unit 701 is further configured to send the resource of the second The network device sends indication information of resources of the first target cell allocated for the terminal device.
  • the future movement information of the terminal device includes predicted at least one of the following: information about the future cell of the terminal device, information about the residence time of the terminal device in the future cell, the The manner in which the terminal device accesses the future cell, whether the terminal device leaves the connected state in the future cell, or the prediction accuracy of the future movement information of the terminal device.
  • the future service information of the terminal device includes predicted at least one of the following: the future service type of the terminal device, the service quality QoS requirement of the future service, and the traffic volume of the future service , or the time information of the future business.
  • the communication unit 701 is further configured to: send feedback information to the second network device, where the feedback information includes indication information of at least one of the following: Information about the actual residence time of the target cell, whether the terminal device actually leaves the connected state in the first target cell, the second reasoning result, or the second target cell.
  • the feedback information is used to optimize or update parameters of a model for determining the first reasoning result.
  • the first reasoning result includes a reasoning result related to the mobility of the primary cell of the terminal device, and/or a reasoning result related to the mobility of the secondary station of the terminal device.
  • the first message when the first inference result includes an inference result related to the mobility of the terminal device's primary cell, the first message includes the terminal device's source secondary station, source secondary cell Indication information whether at least one of the group, the source primary secondary cell, or the source secondary cell needs to be changed.
  • each unit in the device can be implemented in the form of software called by the processing element; they can also be implemented in the form of hardware; some units can also be implemented in the form of software called by the processing element, and some units can be implemented in the form of hardware.
  • each unit can be a separate processing element, or it can be integrated in a certain chip of the device.
  • it can also be stored in the memory in the form of a program, which is called and executed by a certain processing element of the device. Function.
  • all or part of these units can be integrated together, or implemented independently.
  • the processing element mentioned here may also be a processor, which may be an integrated circuit with signal processing capabilities.
  • each operation of the above method or each unit above may be realized by an integrated logic circuit of hardware in the processor element, or implemented in the form of software called by the processing element.
  • the units in any of the above devices may be one or more integrated circuits configured to implement the above method, for example: one or more specific integrated circuits (application specific integrated circuit, ASIC), or, one or Multiple microprocessors (digital signal processor, DSP), or, one or more field programmable gate arrays (field programmable gate array, FPGA), or a combination of at least two of these integrated circuit forms.
  • ASIC application specific integrated circuit
  • DSP digital signal processor
  • FPGA field programmable gate array
  • the units in the device can be implemented in the form of a processing element scheduler
  • the processing element can be a processor, such as a general-purpose central processing unit (central processing unit, CPU), or other processors that can call programs.
  • CPU central processing unit
  • these units can be integrated together and implemented in the form of a system-on-a-chip (SOC).
  • the above unit for receiving is an interface circuit of the device for receiving signals from other devices.
  • the receiving unit is an interface circuit for the chip to receive signals from other chips or devices.
  • the above sending unit is an interface circuit of the device, and is used to send signals to other devices.
  • the sending unit is an interface circuit used by the chip to send signals to other chips or devices.
  • the network device may be an access network device (such as a source base station or a target base station, etc.).
  • the access network device 800 may include one or more DUs 801 and one or more CUs 802.
  • the DU 801 may include at least one antenna 8011, at least one radio frequency unit 8012, at least one processor 8013 and at least one memory 8014.
  • the DU801 is mainly used for transmitting and receiving radio frequency signals, converting radio frequency signals and baseband signals, and processing part of the baseband.
  • the CU 802 may include at least one processor 8022 and at least one memory 8021 .
  • the CU802 part is mainly used for baseband processing, controlling access network equipment, and the like.
  • the DU801 and the CU802 may be physically set together, or physically separated, that is, a distributed base station.
  • the CU802 is the control center of the access network equipment, and can also be called a processing unit, which is mainly used to complete the baseband processing function.
  • the CU 802 may be used to control the access network device to execute the operation procedures related to the access network device in the foregoing method embodiments.
  • the access network device 800 may include one or more radio frequency units, one or more DUs, and one or more CUs.
  • the DU may include at least one processor 8013 and at least one memory 8014
  • the radio frequency unit may include at least one antenna 8011 and at least one radio frequency unit 8012
  • the CU may include at least one processor 8022 and at least one memory 8021.
  • the CU802 can be composed of one or more single boards, and multiple single boards can jointly support a wireless access network (such as a 5G network) with a single access indication, or can separately support wireless access networks of different access standards.
  • Access network (such as LTE network, 5G network or other networks).
  • the memory 8021 and the processor 8022 may serve one or more boards. That is to say, memory and processors can be set independently on each single board. It may also be that multiple single boards share the same memory and processor. In addition, necessary circuits can also be set on each single board.
  • the DU801 can be composed of one or more single boards, and multiple single boards can jointly support a wireless access network (such as a 5G network) with a single access indication, or can respectively support wireless access networks of different access standards (such as a 5G network). LTE network, 5G network or other networks).
  • the memory 8014 and the processor 8013 may serve one or more boards. That is to say, memory and processors can be set independently on each single board. It may also be that multiple single boards share the same memory and processor. In addition, necessary circuits can also be set on each single board.
  • the access network equipment shown in FIG. 8 can implement various processes involving the source base station and the target base station in the foregoing method embodiments.
  • the operations and/or functions of the various modules in the access network device shown in FIG. 8 are respectively for realizing the corresponding processes in FIGS. 3 to 6 in the above method embodiment.
  • system and “network” in the embodiments of the present application may be used interchangeably.
  • “At least one” means one or more, and “plurality” means two or more.
  • “And/or” describes the association relationship of associated objects, indicating that there can be three types of relationships, for example, A and/or B, which can mean: A exists alone, A and B exist simultaneously, and B exists alone, where A, B can be singular or plural.
  • the character “/” generally indicates that the contextual objects are an “or” relationship.
  • “At least one of the following” or similar expressions refer to any combination of these items, including any combination of single or plural items. For example "at least one of A, B or C” includes A, B, C, AB, AC, BC or ABC. And, unless otherwise specified, ordinal numerals such as “first” and “second” mentioned in the embodiments of this application are used to distinguish multiple objects, and are not used to limit the order, timing, priority or importance of multiple objects degree etc.
  • the embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing apparatus to operate in a specific manner, such that the instructions stored in the computer-readable memory produce an article of manufacture comprising instruction means, the instructions
  • the device realizes the function specified in one or more procedures of the flowchart and/or one or more blocks of the block diagram.

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  • Engineering & Computer Science (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Databases & Information Systems (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

L'invention concerne un procédé et un appareil de communication. Au cours du procédé, un second dispositif de réseau envoie un premier message à un premier dispositif de réseau correspondant à une première cellule cible. La première cellule cible est une cellule de service qui est prédite et à laquelle un dispositif terminal peut accéder. Le premier message est utilisé pour indiquer un premier résultat d'inférence. Le premier résultat d'inférence comprend au moins une des prédictions suivantes : de futures informations mobiles du dispositif terminal ; de futures informations de service du dispositif terminal ; ou de futures informations sur une trajectoire mobile du dispositif terminal. Le premier dispositif de réseau peut recommencer une inférence IA ou d'autres opérations en fonction du premier résultat d'inférence reçu, ce qui améliore le taux d'utilisation du premier résultat d'inférence.
PCT/CN2022/110695 2021-08-06 2022-08-05 Procédé et appareil de communication WO2023011655A1 (fr)

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EP22852366.8A EP4369787A1 (fr) 2021-08-06 2022-08-05 Procédé et appareil de communication
US18/432,420 US20240179603A1 (en) 2021-08-06 2024-02-05 Communication method and apparatus

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CN202110900384.2 2021-08-06
CN202110900384.2A CN115707047A (zh) 2021-08-06 2021-08-06 一种通信方法及装置

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CN101365242A (zh) * 2008-08-29 2009-02-11 同济大学 基于移动预测的群体切换方法及系统
CN104902529A (zh) * 2015-04-27 2015-09-09 努比亚技术有限公司 一种网络切换方法、装置及基站
CN108810965A (zh) * 2017-05-05 2018-11-13 华为技术有限公司 一种随机接入资源分配方法及装置

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US20040203831A1 (en) * 2002-04-11 2004-10-14 Khan Moinul H. Reduction of QoS impairment during the hand-off process
CN101365242A (zh) * 2008-08-29 2009-02-11 同济大学 基于移动预测的群体切换方法及系统
CN104902529A (zh) * 2015-04-27 2015-09-09 努比亚技术有限公司 一种网络切换方法、装置及基站
CN108810965A (zh) * 2017-05-05 2018-11-13 华为技术有限公司 一种随机接入资源分配方法及装置

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